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    Predictive analytics in aviation management

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    Authors
    Rampersad-Jagmohan, Melissa
    Wang, Yi
    Issue Date
    2024-02-25
    Subjects
    predictive analytics
    aviation
    predictive maintenance
    strategic information systems management
    
    Metadata
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    Other Titles
    Advanced Manufacturing and Automation XIII
    Abstract
    The aviation industry has undergone significant changes driven by technological advancements and changing consumer demands (Joseph 2023). One area that has seen notable growth is Predictive Analytics (PA), which involves using historical information to determine trends and forecast future occurrences (IBM 2022). Predictive analytics has become increasingly important in the aviation industry and is driven by the need to improve safety, make better decisions and improve passenger satisfaction and experience (RTS Labs 2023). As data plays an increasingly integral role in the industry, predictive analytics will become even more prevalent. The Aviation industry faces several issues, including flight delays and cancellations, unscheduled maintenance and repair, inefficient fuel consumption and passenger dissatisfaction (Awasthi 2018). This paper aims to select a digital technology to enhance the operations of the aviation industry and improve the passenger experience. The chosen digital technology is Predictive Analytics (PA). Following this, the identification of Strategic Information Systems (SIS) opportunities and their impacts will be discussed, considering competitive edge feasibility, risks, and challenges to implementing the chosen technology. Following the analysis, a recommendation will be proposed to implement the PA technology or maintain current operations (Laudon and Laudon 2018).
    Citation
    Rampersad-Jagmohan M, Wang Y (2024) 'Predictive analytics in aviation management', Advanced Manufacturing and Automation XIII (IWAMA 2023) - Shanghai , Springer Science and Business Media Deutschland GmbH.
    Publisher
    Springer Science and Business Media Deutschland GmbH
    URI
    http://hdl.handle.net/10547/626841
    DOI
    10.1007/978-981-97-0665-5_52
    Additional Links
    https://link.springer.com/chapter/10.1007/978-981-97-0665-5_52
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9789819706648
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-981-97-0665-5_52
    Scopus Count
    Collections
    Business and management

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